RATE: Responder Average Treatment Effect

In targeted: Targeted Inference

Responder Average Treatment Effect

Description

Estimation of the Average Treatment Effect among Responders

Usage

RATE(
  response,
  post.treatment,
  treatment,
  data,
  family = gaussian(),
  M = 5,
  pr.treatment,
  treatment.level,
  SL.args.response = list(family = gaussian(), SL.library = c("SL.mean", "SL.glm")),
  SL.args.post.treatment = list(family = binomial(), SL.library = c("SL.mean", "SL.glm")),
  preprocess = NULL,
  efficient = TRUE,
  ...
)

Arguments

response	Response formula (e.g, Y~D*A)
post.treatment	Post treatment marker formula (e.g., D~W)
treatment	Treatment formula (e.g, A~1)
data	data.frame
family	Exponential family for response (default gaussian)
M	Number of folds in cross-fitting (M=1 is no cross-fitting)
pr.treatment	(optional) Randomization probability of treatment.
treatment.level	Treatment level in binary treatment (default 1)
SL.args.response	Arguments to SuperLearner for the response model
SL.args.post.treatment	Arguments to SuperLearner for the post treatment indicator
preprocess	(optional) Data preprocessing function
efficient	If TRUE, the estimate will be efficient. If FALSE, the estimate will be a simple plug-in estimate.
...	Additional arguments to lower level functions

Value

estimate object

Author(s)

Andreas Nordland, Klaus K. Holst

targeted documentation built on Oct. 26, 2022, 1:09 a.m.